Attendance

Was the course useful?

How was the level?

How was the pace?

• Was there anything that was a total game changer for you? (e.g. something you didn’t know before, but will make your work much easier)

• Was there anything that was especially bad? (e.g. really badly explained, really boring, really irrelevant)

• Any other comments

Comments

• The parameter handling and scaling (e.g. converting temperature from Kelvin to °C) is much easier now

• Being able to get wind speed and direction from U and V is really helpful

RRJV

read_point_forecast()

read_point_obs()

join_to_fcst()

det/ens_verify()

S/P

plot_point_verif()

save_point_verif()

shiny_plot_point_verif()

Comments

• It was my first time seeing conditional verification, which will be very useful for analysing performance in specific circumstances

• Stratifying verification by wind direction will be especially useful, as long as you know what the direction in degrees means on the compass ;-)

Non Standard evaluation (NSE)

harp uses NSE for a smoother ride for interactive running

Causes problems for using variables

Embracing variables with {{ }}

Comments

• ‘Build a Script’ was particularly useful as I am not an R expert and the good practises discussed here were very useful

• Managed to code the basics script for point verification for a new task at our institute during the session on point verification

Comments [Good]

Spatial verification was something that I had not worked within HARP of course, so it was useful to identify ways it can easily replace some existing tools

Comments [Not so good]

It would be great if the spatial part was provided in a tidier manner. It is usually the case that the point verification and data ingestion part is prepared before hand and then the code is posted online every day. This does not happen with the spatial part, and there are always last minute developments that would be committed during the week . Also, using the development version in the course might not be the best practice in my opinion, since this version is changing and the functions might change. Would it not be better to use the current stable version instead?

geom_georaster()

ggplot geom for plotting georeferenced rasters

ggplot(t2m, aes(geofield = fcst)) + geom_georaster() + theme_harp_map()

geom_georaster()

map <- get_map(precip_1h$fcst)
ggplot() + 
  geom_polygon(aes(x, y, group = group), data = map, fill = "grey") +
  geom_georaster(
    aes(geofield = fcst), data = precip_1h,
    upscale_method = "downsample", upscale_factor = 4
  ) +
  geom_polygon(
    aes(x, y, group = group), data = map,
    fill = "transparent", colour = "grey20"
  ) + 
  scale_fill_scico(
    "mm", palette = "oslo", trans = "log", direction = -1,
    limits = c(0.125, 64), breaks = seq_double(0.125, 10),
    na.value = "transparent"
  ) +
  facet_wrap(~member, nrow = 2) +
  coord_equal(expand = FALSE) + 
  theme_harp_map()

geom_georaster()

Comments

• The spatial data handling in harp was very impressive and I’ll be using it much more for visualisation going forward

• [Good] Getting more familiar with the visualization capabilities of harp